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Machine Learning Engineer Jobs in Beaverton, OR (NOW HIRING)

We are the Machine Learning Product team at Workday. Our focus is on the application of machine ... Using current programming language and technologies, writes code, completes programming, and ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Data engineer

Beaverton, OR · On-site

$120K - $144K/yr

Data Engineer Primary Responsibilities • Support Data Science team by applying data mining techniques, feature engineering, algorithm optimization and scaling machine learning models in big data ...

Machine Operator

Happy Valley, OR

$18 - $21.25/hr

Machine Operator Join a highly automated, state-of-the-art manufacturing team where you will help ... Engineering. You will have access to tuition reimbursement, online learning through LinkedIn ...

Five (5) years of experience in Data Science / Machine Learning * Strong programming skills in Python * Proven experience with: * Time-series analysis and anomaly detection * Statistical modeling and ...

You will leverage the latest machine learning techniques, and technology to optimize underwriting ... Strong Programming skills in Python and/or R (Python preferred) * Predictive modeling experience ...

You will leverage the latest machine learning techniques, and technology to optimize underwriting ... Strong Programming skills in Python and/or R (Python preferred) * Predictive modeling experience ...

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Machine Learning Engineer information

See Beaverton, OR salary details

$32.8K

$134K

$201.3K

How much do machine learning engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for machine learning engineer in Beaverton, OR is $133,979.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,600.00 and $161,300.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Beaverton, OR? The most popular types of Machine Learning Engineer jobs in Beaverton, OR are:
What are popular job titles related to Machine Learning Engineer jobs in Beaverton, OR? For Machine Learning Engineer jobs in Beaverton, OR, the most frequently searched job titles are:
What cities near Beaverton, OR are hiring for Machine Learning Engineer jobs? Cities near Beaverton, OR with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Beaverton, OR as of July 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $133,979 per year, or $64.4 per hour.

$120K - $170K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago


Job description

Compensation Range:

$120,000.00 - $170,000.00 Annual Salary

Job Description Summary:

We are seeking an Applied AI Engineer to build and deliver practical AI solutions that drive automation, productivity, and business value. This role is focused on turning business needs into working solutions - from intelligent workflows and copilots to agent-based tools and AI-enabled applications. The ideal candidate is both technically strong and highly hands-on, with the ability to design, prototype, build, and deploy scalable solutions that solve real business problems.

Job Description:

Key Responsibilities

  • Build and deploy AI-powered automations and agent-based solutions that improve business processes and productivity.
  • Design and implement practical AI workflows using LLMs, retrieval, tool/function calling, orchestration, multi-agent patterns, integrations, and related technologies.
  • Integrate AI capabilities into enterprise systems, applications, and business processes to support real-world adoption and measurable value.
  • Test, monitor, troubleshoot, and continuously improve deployed AI solutions for reliability, usability, and performance.
  • Collaborate with business and technical stakeholders to refine requirements and translate them into working solutions.
  • Contribute reusable patterns, engineering practices, and responsible AI approaches that support scalable solution delivery.

Skills, Experience, and Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
  • 3+ years of experience in software engineering, AI engineering, machine learning engineering, or similar hands-on technical roles.
  • Hands-on experience building and deploying AI-enabled applications, automations, or intelligent workflows in an enterprise environment, including delivery within defined solution direction and architectural guardrails.
  • Experience with AI frameworks, APIs, and tools for LLMs, retrieval, tool/function calling, orchestration, or multi-agent workflows.
  • Familiarity with frameworks and protocols such as LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, MCP, or similar tools is preferred.
  • Experience with enterprise cloud and AI development platforms such as Microsoft Foundry, Databricks, or similar enterprise ecosystems is preferred.
  • Strong programming and engineering skills, including CI/CD, deployment automation, monitoring, and operational support practices for AI or software solutions.
  • Strong problem-solving, communication, and stakeholder collaboration skills.
  • Construction industry experience is preferred but not required.

Summary of Benefits:

This role is eligible for the following benefits:medical, dental, vision, 401(k) with company matching, Employee Stock Ownership Program (ESOP), individual stock ownership, paid vacation, paid sick leave, paid holidays, bereavement leave, employee assistance program, pre-tax flexible spending accounts, basic term life insurance and AD&D, business travel accident insurance, short and long term disability, financial wellness coaching, educational assistance, Care.com membership, ClassPass fitness membership, and DashPass delivery membership. Voluntary benefits include additional term life insurance, long term care insurance, critical illness and accidental injury insurance, pet insurance, legal plan, identity theft protection, and other voluntary benefit options.

Anticipated Job Application Deadline:

07/31/2026